October 5, 2010

For someone learning about models, two instructive posts from Krugman. One, on the analytical strengths of models in the social sciences (well, economics really, but the general lesson could apply):

If you think in terms of slogans like “free trade good; protectionism evil”, you find it outrageous that a credentialed economist might actually consider trade sanctions on China justified. Sacrilege!

If you think in terms of models, however, you know that the case for free trade is profound, but also conditional: it depends, among other things, on having sufficient policy levers to achieve more or less full employment simultaneously with free trade.

And another on their limitations, and the importance of understanding the empirical intuition behind them:

What’s going on here? I believe that what we’re looking at is people who know their math, but don’t know what it means: they can grind through the equations of their models, but don’t have any feel for what the equations really imply. Confronted with informal discussion that’s grounded in models but not explicitly stated in terms of math, they’re totally baffled. And so they lash out.

He’s talking about economics. Other social sciences that use models, such as political science, are probably less enthralled by their models. I’m hoping to use them in the law-and-society field, but by explicitly adopting a mixed methods design I hope to avoid loosing sight of what it is exactly that I’m attempting to understand via a model.